3.8 Article

Intensity standardization methods in magnetic resonance imaging of head and neck cancer

Journal

PHYSICS & IMAGING IN RADIATION ONCOLOGY
Volume 20, Issue -, Pages 88-93

Publisher

ELSEVIER
DOI: 10.1016/j.phro.2021.11.001

Keywords

MRI; Standardization; Harmonization; Normalization; Quantitative analysis; Head and neck cancer

Funding

  1. National Institutes of Health (NIH) through a Cancer Center Support Grant [P30-CA016672-44]
  2. University of Texas Health Science Center at Houston Center for Clinical and Translational Sciences TL1 Program [TL1TR003169]
  3. American Legion Auxiliary Fellowship in Cancer Research
  4. NIDCR F31 fellowship [1 F31 DE031502-01]
  5. NIH National Institute of Dental and Craniofacial Research (NIDCR) Award [R01DE025248]
  6. NIH NIDCR Award [F31DE029093, R01 DE028290-01, 1R01DE025248-01/R56DE025248]
  7. University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences
  8. Society of Interventional Radiology Foundation Allied Scientist Grant
  9. Dr. John J Kopchick Fellowship
  10. NIH NIDCR Research Supplements [R01DE025248-S02, R01DE028290-S01]
  11. Academic-Industrial Partnership Award [R01 DE028290]
  12. National Science Foundation (NSF), Division of Mathematical Sciences, Joint NIH/NSF Initiative on Quantitative Approaches to Biomedical Big Data (QuBBD) [NSF 1557679]
  13. NIH Big Data to Knowledge (BD2K) Program of the National Cancer Institute (NCI) Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science Award [1R01CA214825]
  14. NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program [1R01CA218148]
  15. UT MD Anderson CCSG Radiation Oncology and Cancer Imaging Program [P30CA016672]
  16. NIH/NCI Head and Neck Specialized Programs of Research Excellence (SPORE) Developmental Research Program Award [P50 CA097007]
  17. National Institute of Biomedical Imaging and Bioengineering (NIBIB) Research Education Program [R25EB025787]
  18. Elekta AB
  19. Dutch organization NWO ZonMw

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The study emphasizes the importance of intensity standardization in quantitative analysis of head and neck cancer MRI. A workflow based on healthy tissue ROI analysis was developed to evaluate intensity standardization methods. Results showed significant impact of intensity standardization methods on consistency of MRI images in heterogeneous acquisition parameters, while the impact was minimal in homogeneous acquisition parameters.
Background and Purpose: Conventional magnetic resonance imaging (MRI) poses challenges in quantitative analysis because voxel intensity values lack physical meaning. While intensity standardization methods exist, their effects on head and neck MRI have not been investigated. We developed a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluated intensity standardization methods for MRI of head and neck cancer (HNC) patients. Materials and Methods: Two HNC cohorts (30 patients total) were retrospectively analyzed. One cohort was imaged with hetemgenous acquisition parameters (HET cohort), whereas the other was imaged with homogenous acquisition parameters (HOM cohort). The standard deviation of cohort-level normalized mean intensity (SD NMIc), a metric of intensity consistency, was calculated across ROIs to determine the effect of five intensity standardization methods on T2-weighted images. For each cohort, a Friedman test followed by a post-hoc Bonferroni-corrected Wilcoxon signed-rank test was conducted to compare SD NMI(c )among methods. Results: Consistency (SD NMIc across ROIs) between unstandardized images was substantially more impaired in the HET cohort (0.29 +/- 0.08) than in the HOM cohort (0.15 +/- 0.03). Consequently, corrected p-values for intensity standardization methods with lower SD NMI, compared to unstandardized images were significant in the HET cohort (p < 0.05) but not significant in the HOM cohort (p > 0.05). In both cohorts, differences between methods were often minimal and nonsignificant. Conclusions: Our findings stress the importance of intensity standardization, either through the utilization of uniform acquisition parameters or specific intensity standardization methods, and the need for testing intensity consistency before performing quantitative analysis of HNC MRI.

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